public void TestBernoulliPointEstimator()
{
var distribution = new Bernoulli(0.25);
Assert.False(distribution.GetMode());
Assert.False(PointEstimator.GetEstimate(distribution, Metrics.ZeroOneError)); // Mode
Assert.False(distribution.GetMean() >= 0.5);
Assert.False(PointEstimator.GetEstimate(distribution, Metrics.SquaredError)); // Mean
Assert.False(PointEstimator.GetEstimate(distribution, Metrics.AbsoluteError)); // Median = Mode
distribution = new Bernoulli(0.5);
Assert.True(distribution.GetMode());
Assert.True(PointEstimator.GetEstimate(distribution, Metrics.ZeroOneError)); // Mode
Assert.True(distribution.GetMean() >= 0.5);
Assert.True(PointEstimator.GetEstimate(distribution, Metrics.SquaredError)); // Mean
Assert.True(PointEstimator.GetEstimate(distribution, Metrics.AbsoluteError)); // Median = Mode
distribution = new Bernoulli(0.6);
Assert.True(distribution.GetMode());
Assert.True(PointEstimator.GetEstimate(distribution, Metrics.ZeroOneError)); // Mode
Assert.True(distribution.GetMean() >= 0.5);
Assert.True(PointEstimator.GetEstimate(distribution, Metrics.SquaredError)); // Mean
Assert.True(PointEstimator.GetEstimate(distribution, Metrics.AbsoluteError)); // Median = Mode
Assert.Throws <ArgumentNullException>(() => PointEstimator.GetEstimate(distribution, null));
// Test generic representation of distribution
var genericDistribution = new Dictionary <bool, double> {
{ true, 0.25 }, { false, 0.75 }
}; // Order matters!
Assert.False(PointEstimator.GetEstimate(genericDistribution, Metrics.ZeroOneError)); // Mode
Assert.False(PointEstimator.GetEstimate(genericDistribution, Metrics.SquaredError)); // Mean
Assert.False(PointEstimator.GetEstimate(genericDistribution, Metrics.AbsoluteError)); // Median = Mode
genericDistribution = new Dictionary <bool, double> {
{ true, 0.5 }, { false, 0.5 }
};
Assert.True(PointEstimator.GetEstimate(genericDistribution, Metrics.ZeroOneError)); // Mode
Assert.True(PointEstimator.GetEstimate(genericDistribution, Metrics.SquaredError)); // Mean
Assert.True(PointEstimator.GetEstimate(genericDistribution, Metrics.AbsoluteError)); // Median = Mode
genericDistribution = new Dictionary <bool, double> {
{ true, 0.6 }, { false, 0.4 }
};
Assert.True(PointEstimator.GetEstimate(genericDistribution, Metrics.ZeroOneError)); // Mode
Assert.True(PointEstimator.GetEstimate(genericDistribution, Metrics.SquaredError)); // Mean
Assert.True(PointEstimator.GetEstimate(genericDistribution, Metrics.AbsoluteError)); // Median = Mode
Assert.Throws <ArgumentNullException>(() => PointEstimator.GetEstimate(distribution, null));
}
/// <summary>
/// Prints the prediction.
/// </summary>
/// <param name="index">Index.</param>
/// <param name="posteriorActivity">Posterior activity.</param>
/// <param name="label">If set to <c>true</c> label.</param>
/// <param name="score">Score.</param>
public static void PrintPrediction(int index, Bernoulli posteriorActivity, bool label, double score)
{
Console.WriteLine("{0,3}, Score: {1,4:N2}, Bayes Point {2:N2}, Label {3,5}, Predicted {4,5}, Correct {5,5}",
index, score, posteriorActivity.GetMean(), label, posteriorActivity.GetMode(), label == posteriorActivity.GetMode());
}